1. Field of the Invention
The present invention relates to an information recording and reproducing apparatus and evaluation method and an information recording medium, and more particularly, to improvement of an information recording and reproducing apparatus and an evaluation method for reproducing a signal recorded in an information recording medium and evaluating the reproduction signal.
2. Description of the Related Art
Signal processing in an information recording and reproducing apparatus includes PRML (Partial Response and Maximum Likelihood) identification scheme. A technique associated with evaluation of a signal quality in a system using the PRML identification scheme includes SAMER (SAM Error Rate) available from Sharp Co., Ltd., disclosure information ISOM' 01 (International Symposium On Optical Memory 2001) Technical Digest P272).
In the PRML identification scheme, the PR (Partial Response) characteristics according to recording and reproducing characteristics are employed. As an example, a description of PR (1, 2, 2, 1) characteristics will be given below. In the case of the PR (1, 2, 2, 1) characteristics, a 4-tap FIR (Finite Impulse Response) filter whose tap coefficient is 1, 2, 2, 1 is employed. When a series of 00010000, for example, is input to the FIR filter, the output is obtained as 00012210. Similarly, when 000110000 is input, 000134310 is output. When 0001110000 is input, 000135531 is output. When 00011110000 is input, 00013565310 is output. These outputs are ideal signals in the bit series. Next, a Viterbi decoder compares an equalized signal output from the filter (equalizer) and an ideal signal with each other, and selects the closest series. A concept of Euclidean distance is introduced. A Euclidean distance E2 indicates a distance between signals, and if signals SA and SB are assumed, they are defined as follows.E2=Σ(SA−SB)2 
Now, a more specific description will be given by using numerals. Assume that the following reproduction signals S1 and S2 are PR equalized.S1=[5.9 6.1 5.9 4.9 2.9 0.9 0.1 0.0 0.1]S2=[5.8 6.0 5.8 4.7 2.7 1.1 0.2 0.1 0.2]
Euclidean distance between the ideal signals of all patterns is calculated in response to the two reproduction signals S1 and S2. As a result of comparing Euclidean distance, assuming that the ideal signal of which Euclidean distance between S1 and S2 is minimal is obtained as [6 6 6 5 3 1 0 0 0] (this is an output of the above FIR filter of [1 1 1 1 1 1 0 0 0 0 0 0]), and the next minimum ideal signal is obtained [6 6 5 3 1 0 0 0 0] (similarly, an output of [1 1 1 1 1 0 0 0 0 0 0 0], Euclidean distances respectively are obtained as follows.
With respect to S1 Emin2=(6−5.9)2+(6−6.1)2+(6−5.9)2+ . . . +(0−0.1)2=0.08Enext2=(6−5.9)2+(6−6.1)2+(6−5.9)2+ . . . +(0×0.1)2=8.88
With respect to S2 Emin2=(6−5.8)2+(6−6.0)2+(6−5.8)2+ . . . +(0−0.2)2=0.36Enext2=(6−5.8)2+(6−6.0)2+(6−5.8)2+ . . . +(0−0.2)2=7.76
where S1 is Enext2−Emin2=8.8, and S2 is Enext2−Emin2=7.4.
As a result, it can be said that S1 is more hardly mistaken than S2 because it is large. In this way, SAM calculating device carries out calculation in accordance with the above described procedures every time a reproduction signal is input from the equalizer. Then, the calculation result of Enext2−Emin2 is accumulated, and its distribution is calculated, thereby carrying out signal evaluation.
On the other hand, the SAMER calculating device calculates an expected bER (bit error rate) from the SAM distribution. As described above, the SAM distribution is obtained by Enext2−Emin2. Since the Viterbi decoder selects an ideal signal which is the closest to an equalization signal input from an equalizer, a relationship between Enext2 and Emin2 is always obtained as Enext2>Emin2. However, an identification error occurs in the case where Enest is mistakenly selected instead of Emin. At this time, a relationship is obtained as Enext2<Emin2 In the SAM distribution, this range is unlikely to be established. However, assuming that a portion of distribution which is lower than “μ” is a normal distribution, the standard deviation “σ” and average “μ” are approximated by Gaussian probability density function, thereby estimating a range of Enext2<Emin2. A problem of SAM and SAMER is, when a group of bit series whose Euclidean distance is minimal is created in response to a bit series, Euclidean distance which is minimal for each group is different from another. Thus, when a distribution of Enext2−Emin2 has been calculated, such distribution is divided in plurality, and is not occasionally obtained as an evaluation value. Further, in the range of “μ” or less of SAMER, there may be a case in which the normality of distribution is destroyed, and there is a possibility that an error occurs between bER estimated at this time and actual bER. In addition, every time a 1-channel reproduction signal is input, the ideal signals of all series and its Euclidean distance are calculated, and a calculation quantity for selecting the minimum value and next minimal value is increased.